\begin{abstract}
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Brain-computer interfaces (BCIs) are revolutionizing the interaction of man with machine by allowing one to control an external device using brain signals alone \citep{wolpaw2002brain}. % (Wolpaw, et al 2002). 
This technology will allow individuals with severe neuromuscular disabilities to effectively communicate with their environment. BCIs typically acquire brain signals using electroencephalography (EEG), intracortical single unit recordings, or electrocorticography (ECoG), which are then converted into outputs that control the external device. An important barrier to practical implementation of BCI technology is the inability of the user to switch the BCI on and off using their brain signals alone. An obvious scenario when such a switch will be necessary is when the user is asleep versus when they are awake. In this work, we identify and characterize the anatomic and spectral features of subdural ECoG recordings required for accurate classification of sleep and wake states.
\end{abstract}